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Title: Estimation of full-field dynamic strains from digital video measurements of output-only beam structures by video motion processing and modal superposition

Journal Article · · Structural Control and Health Monitoring
DOI:https://doi.org/10.1002/stc.2408· OSTI ID:1558040
ORCiD logo [1];  [2];  [3];  [2]; ORCiD logo [4]; ORCiD logo [4]
  1. Argonne National Lab. (ANL), Lemont, IL (United States)
  2. Chonnam National Univ., Gwangju (South Korea)
  3. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
+ Show Author Affiliations

Strain is an necessary quantity to characterize local structural behaviors and directly correlates with structural damage initiation and development that is within local regions. Strain measurement at high spatial resolution (density) locations is thus required to characterize local structural behaviors and detect potential local damage. Traditional contact-type strain gauges are mostly discrete point-wise sensors that can only be placed in a limited number of positions. Distributed optical fiber sensing techniques can measure strains at spatially dense measurement points, but their instrumentation is a time- and labor-intensive process associated with the issue of the fragility of fibers. Noncontact optical measurement techniques, such as a family of interferometry techniques using laser beams (e.g., laser Doppler vibrometers), can provide vibration measurement at high density spatial points without the need to install sensors on the structure. Yet, these measurement devices are active sensing methods that are relatively expensive and vulnerable to ambient motion. Photogrammetry is an alternative noncontact optical measurement method using (passive) white-light imaging of digital video cameras that are relatively low-cost, agile, and provides simultaneous measurements at high spatial density locations where every pixel becomes a measurement point. Among others, digital image correlation can achieve full-field deformation measurements and subsequently estimate the full-field strains. However, it is computationally extensive. This research develops a new efficient approach to estimate the full-field (as many measurement points as the pixel number of the video frame on the structure) dynamic strains at high-spatial (pixel)-resolution/density location points from the digital video measurement of output-only vibrating structures. The developed approach is based on phase-based video motion estimation and modal superposition of structural dynamic response. Moreover, the method is augmented by a high-fidelity finite element model, which is updated with the full-field experimental modal parameters “blindly” identified from the video measurement of the output-only structure. Laboratory experiments are conducted to validate the method on a bench-scale cantilever beam structure. Results demonstrate that the full-field dynamic strain estimated by the developed approach from the video measurement of the output-only vibrating beam match very well those directly measured by the strain gauges (at discrete measurement points). Some factors associated with the effectiveness of the method are experimentally studied and discussed.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
89233218CNA000001; 20150708PRD2
OSTI ID:
1558040
Alternate ID(s):
OSTI ID: 1542683
Report Number(s):
LA-UR-17-24265
Journal Information:
Structural Control and Health Monitoring, Vol. 26, Issue 10; ISSN 1545-2255
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 15 works
Citation information provided by
Web of Science

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Cited By (1)

Displacement, Strain and Failure Estimation for Multi-Material Structure Using the Displacement-Strain Transformation Matrix journal January 2020

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47 OTHER INSTRUMENTATION
dynamic strain
full‐field measurement
model updating
operational modal analysis
photogrammetry
video processing